I find it strange to see people writing articles like this as if everyone has used AI for decades. I've programmed for decades. I thought I retired three years ago but got an offer I couldn't refuse. Already there were little things I'd forgotten how to use.
Over the past six months I tried using Claude, chatgpt, Grok and Gemini. At best I got reminders of how things worked. People online say they use them to write their code. The code they supplied to me has NEVER worked or was so convoluted that I threw it away and did it myself.
At most, I use these tools as search engines. Even then some references are poor.
I'm starting to think this is becoming a sad, sad world and AI is just the new TV of the programming world.
> The code they supplied to me has NEVER worked or was so convoluted that I threw it away and did it myself.
For me, it's like reading prose with "Not X, not Y, just Z": it's technically correct, but grates like fingernails on a chalkboard.
I have real trouble sometimes, reading what SOTA (Fable, etc) generate - no isolation or partitioning at all.
The worst was the planning an AI does. When I plan something, it'll be split according to data structures "An object to hold this, an intermediary for the obejct to talk to ORM, a serialiser for it that does this", etc.
The "plans" from SOTA are sometimes just hilarious. It'll go "phase one, implement these user-facing features. Phase two, implement those user-facing features", etc.
That's not a plan, it's an aspiration! A roadmap maybe. A plan, in my way of working, is a blueprint of where all the data goes, with algorithms connecting them. With AI, the data is incidental, the algorithms are incidental, only the goal (in the form of tests) remain. It'll work out some spur-of-the-moment idea around data at the time of writing.
So yeah, I do what you do and throw their stuff away. Currently having more success laying down a skeleton manually and then asking them to add a single feature at a time.
That's with SOTA models as of September-26-2026.
i'm using LLMs/GenAI to do one thing: write unit tests.
since i really don't follow the idea of "writing unit tests first", i implement the feature, test as a user, and then use LLMLs to write the basic unit test. then, i will write more tests to make sure i'm covering everything.
feels like an ok-ish compromise because LLMs can do some ok job with defensive code, while i maintain the main implementation and more advanced test scenarios.
assimpleaspossi · · focus · HN ↗
Over the past six months I tried using Claude, chatgpt, Grok and Gemini. At best I got reminders of how things worked. People online say they use them to write their code. The code they supplied to me has NEVER worked or was so convoluted that I threw it away and did it myself.
At most, I use these tools as search engines. Even then some references are poor.
I'm starting to think this is becoming a sad, sad world and AI is just the new TV of the programming world.
lelanthran · · focus · HN ↗
For me, it's like reading prose with "Not X, not Y, just Z": it's technically correct, but grates like fingernails on a chalkboard.
I have real trouble sometimes, reading what SOTA (Fable, etc) generate - no isolation or partitioning at all.
The worst was the planning an AI does. When I plan something, it'll be split according to data structures "An object to hold this, an intermediary for the obejct to talk to ORM, a serialiser for it that does this", etc.
The "plans" from SOTA are sometimes just hilarious. It'll go "phase one, implement these user-facing features. Phase two, implement those user-facing features", etc.
That's not a plan, it's an aspiration! A roadmap maybe. A plan, in my way of working, is a blueprint of where all the data goes, with algorithms connecting them. With AI, the data is incidental, the algorithms are incidental, only the goal (in the form of tests) remain. It'll work out some spur-of-the-moment idea around data at the time of writing.
So yeah, I do what you do and throw their stuff away. Currently having more success laying down a skeleton manually and then asking them to add a single feature at a time.
That's with SOTA models as of September-26-2026.
fernandotakai · · focus · HN ↗
since i really don't follow the idea of "writing unit tests first", i implement the feature, test as a user, and then use LLMLs to write the basic unit test. then, i will write more tests to make sure i'm covering everything.
feels like an ok-ish compromise because LLMs can do some ok job with defensive code, while i maintain the main implementation and more advanced test scenarios.